Bloat Free Genetic Programming versus Classification Trees for Identification of Burned Areas in Satellite Imagery

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{Silva:2010:EvoIASP,
  author =       "Sara Silva and Maria J. Vasconcelos and 
                 Joana B. Melo",
  title =        "Bloat Free Genetic Programming versus Classification
                 Trees for Identification of Burned Areas in Satellite
                 Imagery",
  booktitle =    "EvoIASP",
  year =         "2010",
  editor =       "Cecilia {Di Chio} and Stefano Cagnoni and 
                 Carlos Cotta and Marc Ebner and Aniko Ekart and 
                 Anna I. Esparcia-Alcazar and Chi-Keong Goh and 
                 Juan J. Merelo and Ferrante Neri and Mike Preuss and 
                 Julian Togelius and Georgios N. Yannakakis",
  volume =       "6024",
  series =       "LNCS",
  pages =        "272--281",
  address =      "Istanbul",
  month =        "7-9 " # apr,
  organisation = "EvoStar",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-12238-5",
  DOI =          "doi:10.1007/978-3-642-12239-2_28",
  size =         "10 pages",
  abstract =     "This paper compares Genetic Programming and
                 Classification Trees on a problem of identification of
                 burned areas in satellite imagery. Additionally, it
                 studies how the most recently recognized bloat control
                 technique, Operator Equalisation, affects the quality
                 of the solutions provided by Genetic Programming. The
                 merit of each approach is assessed not only by its
                 classification accuracy, but also by the ability to
                 predict the correctness of its own classifications, and
                 the ability to provide solutions that are human
                 readable and robust to data inaccuracies. The results
                 reveal that both approaches achieve high accuracy with
                 no overfitting, and that Genetic Programming can reveal
                 some surprises and offer interesting advantages even on
                 a simple problem so easily tackled by the popular
                 Classification Trees. Operator Equalisation proved to
                 be crucial.",
  notes =        "EvoIASP'2010 held in conjunction with EuroGP'2010
                 EvoCOP2010 EvoBIO2010",
  affiliation =  "INESC-ID Lisboa, Portugal",
}

Genetic Programming entries for Sara Silva Maria Jose Vasconcelos Joana B Melo

Citations